Facial emotion recognition on a dataset using Convolutional Neural Network

BildiriAçık Erişim

Özet

Nowadays, deep learning is a technique that takes place in many computer vision related applications and studies. While it is put in the practice mostly on content based image retrieval, there is still room for improvement by employing it in diverse computer vision applications. In this study, we aimed to build a Convolutional Neural Network (CNN) based Facial Expression Recognition System (FER), in order to automatically classify expressions presented in Facial Expression Recognition (FER2013) database. Our presented CNN achieved % 57.1 success rate on FER2013 database.

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RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/670Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1109/idap.2017.8090281Yayıncı resmi DOI adresi
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Atıflar
Scopus
68
OpenAlex
83
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorTümen, Vedat
dc.contributor.authorSöylemez, Ömer Faruk
dc.contributor.authorErgen, Burhan
dc.date.accessioned2026-10-28T14:53:31.422276541Z
dc.date.available2026-10-28T14:53:31.422276541Z
dc.date.issued2017
dc.description.abstractNowadays, deep learning is a technique that takes place in many computer vision related applications and studies. While it is put in the practice mostly on content based image retrieval, there is still room for improvement by employing it in diverse computer vision applications. In this study, we aimed to build a Convolutional Neural Network (CNN) based Facial Expression Recognition System (FER), in order to automatically classify expressions presented in Facial Expression Recognition (FER2013) database. Our presented CNN achieved % 57.1 success rate on FER2013 database.
dc.identifier.articlenumber8090281
dc.identifier.doi10.1109/idap.2017.8090281
dc.identifier.isbn978-153861880-6
dc.identifier.scopus2-s2.0-85039912842
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/670
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.conference2017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017
dc.relation.ispartofIDAP 2017 - International Artificial Intelligence and Data Processing Symposium
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectConvolution neural networks
dc.subjectDeep learning
dc.subjectFacial expression recognition
dc.subjectImage classification
dc.subject.otherArtificial intelligence
dc.subject.otherClassification (of information)
dc.subject.otherComputer vision
dc.subject.otherContent based retrieval
dc.subject.otherConvolution
dc.subject.otherData handling
dc.subject.otherDeep learning
dc.subject.otherImage classification
dc.subject.otherImage enhancement
dc.subject.otherImage retrieval
dc.subject.otherNeural networks
dc.subject.otherComputer vision applications
dc.subject.otherContent based image retrieval
dc.subject.otherConvolution neural network
dc.subject.otherConvolutional neural network
dc.subject.otherFacial emotions
dc.subject.otherFacial expression recognition
dc.subject.otherFace recognition
dc.titleFacial emotion recognition on a dataset using Convolutional Neural Network
dc.typeConference Object
rdl.citation.openalex83
rdl.citation.scopus68
rdl.conference.date16 September 2017 through 17 September 2017
rdl.conference.placeMalatya
rdl.oa.statusgreen
rdl.oa.urlhttps://hdl.handle.net/11508/45743
rdl.source.indexSCOPUS